?Knowledge economy? as a concept describes a stage of socio-economic development, when knowledge become a major growth factor. In modern economy, it can be associated with processes of knowledge acquiring, creation and dissemination; its main agents are educational, scientific organizations and innovative business. In conditions of oil prices falling and sanctions, it is important to identify the Russian regions, where knowledge economy is forming, as new areas of growth. Another aim was to estimate whether economic growth of 2000s promote knowledge economy formation. We used methodology of World Bank with some modifications according to available statistics. The Russian knowledge economy index (RKEI) consisted of four blocks: the level of economic development (GRP growth rate and GRP per capita), education and human capital (number of students per capita and the average number of education years for employees), science and innovation (number of researchers and PCT-applications per capita) and information infrastructure (number of cell phones and computers with Internet access per capita). Since the performance of education and science are relatively stable for the Russian regions, characteristics of GRP and information infrastructure, which grew throughout the 2000s, hold the largest share in the variation of the RKEI. We used calculation of the average rank index (measured from to 10), according to the formula: Ri = 10*(Rlow / R), where Ri is a desired figure, Rlow is a number of regions with a lower rank, R is the total number of regions. The calculation was carried out for the whole period from 1998 to 2012 to review the dynamics. The highest level of the RKEI in 1998 (in descending order) was observed in Moscow (6.5) and St. Petersburg (5.9), Tomsk (4.5), Moscow (4.5), Samara (3.6), Khabarovsk (3.48), Primorsky (3.4) and Novosibirsk (3.3) regions; in 2012 the leaders were St. Petersburg (8.8), Moscow (8.7), Tomsk (8.3), Samara (8.1) regions, Tatarstan (8) and Novosibirsk (7.95) region. The areas with the most diversified economy are among the leaders; monospecialized regions (agriculture, mining) are among the laggards. The RKEI increased for all regions during the period, especially for low rank regions (<4: the North Caucasus and the Far East). Voronezh and Tyumen regions, Tatarstan and Bashkortostan have the highest RKEI growth rates (2012/1998) among high rank regions (>5). These regions established more innovative infrastructure and form a better investment climate. All regions have experienced the negative effects of the crisis in 2009, especially Moscow agglomeration. As a result, Moscow gave the leadership in the RKEI to St. Petersburg in 2010 and Moscow region left the top ten leading regions in 2011. The methodology allows us to track the RKEI framework for every region via the radar chart to identify problem areas and competitive advantages.
